Personalized learning in iSTART: Past modifications and future design

Abstract

Computer-based learning environments (CBLEs) provide unprecedented opportunities for personalized learning at scale. One such system, iSTART (Interactive Strategy Training for Active Reading and Thinking) is an adaptive, game-based tutoring system for reading comprehension. This paper describes how efforts to increase personalized learning have improved the system. It also provides results of a recent implementation of an adaptive logic that increases or decreases text difficulty based on students’ performance rather than presenting texts randomly. High school students who received adaptive text selection showed increased sense of learning. Adaptive text selection also resulted in greater pre-training to post-training comprehension test gains, especially for less-skilled readers. The findings demonstrate that system-driven, just-in-time support consistent with the goals of personalized learning benefit the efficacy of computer-based learning environments.     

Multimedia augmented m-learning: Issues,trends and open challenges

The advancement in mobile technology and the introduction of cloud computing systems enable the use of educational materials on mobile devices for a location- and time-agnostic learning process. These educational materials are delivered in the form of data and compute-intensive multimedia-enabled learning objects. Given these constraints, the desired objective of mobile learning (m-learning) may not be achieved. Accordingly, a number of m-learning systems are being developed by the industry and academia to transform society into a pervasive educational institute. However, no guideline on the technical issues concerning the m-learning environment is available. In this study, we present a taxonomy of such technical issues that can impede the life cycle of multimedia-enabled m-learning applications. The taxonomy is devised based on the issues related to mobile device heterogeneity, network performance, content heterogeneity, content delivery, and user expectation. These issues are discussed, along with their causes and measures, to achieve solutions. Furthermore, we identify several trending areas through which the adaptability and acceptability of multimedia-enabled m-learning platforms can be increased. Finally, we discuss open challenges, such as low complexity encoding, data dependency, measurement and modeling, interoperability, and security as future research directions.     

构建现代信息服务中的人文精神

论述了南开大学图书馆在信息服务中构建人文精神的具体做法、体会与收效。     

网站个性化服务研究

文章针对电子商务网站个性化的需求,着重分析了网站个性化服务的内涵、个性化服务策略和网站个陛化服务发展的现状及前景。     

全文电子期刊个性化服务应用研究

全文电子期刊数据库的个性化服务,是指数据库提供者基于Web数据库技术,根据用户特殊要求或特定情况,提供给用户所需的有针对性的信息,或指数据库的这一系统功能。探讨了它的特点和种类。图5。参考文献4。     

个性化教与个性化学

个性化教育的实现,是靠教师的个性化教与学生的个性化学来完成的,但中国教育的弊端就是个性化的缺失。如何解决教和学的创新性是求达个性化的有效途径。大学的教的个性化体现在讲学的研究化、理性化、艺术化;大学学的个性化体现在探索性、实践性、创新性。唯如此,个性化的高等教育才会出现。     

小学生到底喜欢什么样的学习资源*--梅耶多媒体学习原则对数字原住民适用性的实证研究

根据资源偏好和学习难度为学习者提供个性化资源,是数字教材应该具备的功能。上世纪末梅耶等人提出的多媒体学习原则,曾在学习资源设计与开发中发挥了重要的指导作用。那么为数字原住民设计数字教材时,这些原则是否依然适用？该文以72名小学生作为被试,研究他们对资源类型、组合方式和难度的学习偏好,从而验证梅耶理论对数字原住民的适用性。结果发现被试的偏好选择与梅耶的多媒体学习原则基本吻合,但也出现了一些偏差。该文的结论为数字教材中个性化学习资源推送策略提供了实证基础。     

基于社交网络的个性化知识服务模型研究

通过对社交网络所产生的海量用户以及数据的挖掘与分析,判断用户不同的特征与喜好,从而为用户定制个性化知识服务,达到用户的需求,增强其对产品与服务的使用黏性,这不仅满足了企业的商业目的,同时也提高了用户的满意度。论文在深入了解我国社交网络的运营模式、分析社交网络中用户行为特征的前提下,提出从用户兴趣模型出发的个性化知识服务,并建立了基于个人兴趣和兴趣传播推荐的个性化知识服务模型。     

高校图书馆基层党组织个性化服务创建的探索

加强基层服务型党组织建设是落实党的路线方针政策和各项工作任务的重要保障。高校图书馆基层党组织通过个性化服务创建活动,有助于不断拓宽图书馆的服务领域、开创图书馆个性化的服务载体、完善图书馆个性化的服务功能,推进图书馆服务模式的创新,对于提升读者的满意度、为高校提供信息保障和科研支撑有重大意义。     

高校图书馆个性化信息推荐服务的研究与发展

在网络高速化发展的今天，用户对信息的需求不再是大量漫无边际的信息，而是呈现出个性化、多样性和复杂性的特点。高校图书馆应拓展自己的服务模式，迎合个性化信息的需求，才能数字化浪潮中占有一席之地。